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• Cloud–Edge Collaborative Image Recognition Task Offloading: A Federated Learning–Driven Framework for Training–Inference Collaboration and Resource Optimization
  crossref 2025-11-03T03:35:12Z 置信度 0.70
• A Fused Inference Design for Pattern-Based Sparse CNN on Edge Devices
  crossref Jia Guo, Radu Teodorescu, Gagan Agrawal 2022-01-24T21:08:34Z 置信度 0.70
• Energy-Efficient Computer Systems: RISC-V Extensions for Machine Learning Inference at IoT's Edge Computing
  crossref Ben Sujin, Sangeetha M 2026-02-06T06:04:41Z 置信度 0.70
• Deep Reinforcement Learning for Containerized Edge Intelligence Inference Request Processing in IoT Edge Computing
  Edge intelligence (EI) refers to a set of connected systems and devices for artificial intelligence (AI) data collected and learned near the data collection site. The EI model inference phase has been improved through edge caching technologies such as intellig…
  openalex Lionel Nkenyereye, Kang-Jun Baeg, Wan-Young Chung, Kang‐Jun Baeg 等 2023-09-29 置信度 0.72 Computer scienceEdge computingProvisioningInferenceContainer (type theory)
• Towards Efficient Inference and Training of Deep Neural Networks on Edge Devices
  crossref Kun Wang 2026-06-01T15:54:37Z 置信度 0.70
• AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing
  crossref Hadjer Benmeziane, Corey Lammie, Irem Boybat, Malte Rasch 等 2023-09-01T17:24:43Z 置信度 0.70
• Resilient Inference for Personalized Federated Learning in Edge Computing Environments
  crossref Ke Xiao, Qiyuan Wang, Christos Anagnostopoulos, Kevin Bryson 2025-12-01T18:24:05Z 置信度 0.70
• Energy Efficient and QoS-Aware Model Selection for DNN Inference in Edge Intelligence
  crossref Hajar Siar, Erik Elmroth 2026-01-20T20:37:16Z 置信度 0.70
• microGEMM: An Effective CNN-Based Inference Acceleration for Edge Computing
  crossref Zheng Liu, Wei Chen, Kai Qian, Haodong Lu 等 2023-10-23T13:54:10Z 置信度 0.70
• Evolutionary Feature Reduction and Edge-Optimized CNN Inference for Large-Scale IoT DDoS Detection
  The rapid proliferation of Internet of Things (IoT) deployments has introduced significant security vulnerabilities, particularly due to Distributed Denial-of-Service (DDoS) attacks launched through compromised IoT botnets. Real-time detection of such attacks …
  crossref Pravir Chitre, Premkumar Sivakumar 2026-08-10T11:15:00Z 置信度 0.70
• Research on the Application of Rule Inference Technology in Intelligent Edge-Terminal Scenarios
  crossref Yuwei Chen, Jiehao Chen, Jie Shi 2025-07-02T17:40:38Z 置信度 0.70
• Condition Monitoring of Oil-immersed Transformers Using AI Edge Inference for Incipient Fault Prediction: A case study
  crossref George Yogo Odongo, Richard Musabe, Damien Hanyurwimfura, Abubakar Diwani 2022-10-03T20:40:12Z 置信度 0.70
• [SoK] Systematizing Inference Placement For Deep Learning Across Edge And Cloud Platforms: A Multi-Objective Optimization Perspective
  Edge intelligent applications like VR/AR and language model based chatbots have become widespread with the rapid expansion of IoT and mobile devices. However, constrained edge devices often cannot serve the increasingly large and complex deep learning (DL) mod…
  crossref Zongshun Zhang, Ibrahim Matta 2026-01-26T07:03:05Z 置信度 0.70
• The Razor's Edge: Symbolic‐Structuralist Archeology and the Expansion of Archeological Inference
  In this two‐part article, Watson summarizes and discusses a number of new themes in the literature on archeological theory with critical emphasis on symbolic‐structural approaches. Fotiadis comments by applying a structuralist analysis to Watson's argument.
  crossref Patty Jo Watson, Michael Fotiadis 2004-11-23T22:32:18Z 置信度 0.70
• SneakPeek: Data-Aware Model Selection and Scheduling for Inference Serving on the Edge
  crossref Joel Wolfrath, Daniel Frink, Abhishek Chandra 2026-01-13T16:19:00Z 置信度 0.70
• A Flash-Based Reconfigurable QCNN Inference Accelerator for Edge Applications
  crossref Kyler R. Scott, Sunil P. Khatri 2026-01-14T20:39:56Z 置信度 0.70
• Adaptive joint configuration optimization for collaborative inference in edge-cloud systems
  crossref Zheming Yang, Wen Ji, Zhi Wang 2024-04-04T01:02:00Z 置信度 0.70
• A likelihood-based framework for demographic inference from genealogical trees
  Abstract The demographic history of a population drives the pattern of genetic variation and is encoded in the gene-genealogical trees of the sampled alleles. However, existing methods to infer demographic history from genetic data tend to use relatively low-d…
  crossref Caoqi Fan, Jordan L. Cahoon, Bryan L. Dinh, Diego Ortega-Del Vecchyo 等 2023-10-13T21:35:12Z 置信度 0.70
• Robust Machine Learning Inference from X-Ray Absorption Near Edge Spectra through Featurization
  X-ray absorption spectroscopy (XAS) is a powerful tool for probing local structures, oxidation states, and electronic properties of functional materials. Based on energy proximity to the absorption edge, spectra are categorized into XANES (near-edge) and EXAFS…
  crossref Yiming Chen, Shyue Ping Ong, Maria Chan 2025-11-24T08:00:53Z 置信度 0.70
• CIS: Checkpointed Inference for Data Drift-Resilient Model Serving at Edge Servers
  crossref Sudipta Saha Shubha, Haiying Shen, Ganesh Ananthanarayanan 2026-01-13T16:19:00Z 置信度 0.70
• Pruned Graph Neural Networks for Efficient Edge Classification and Fast Inference
  crossref Henry Paschke, James Gaboriault-Whitcomb, Carson Zoccole, Alina Lazar 2025-01-16T18:31:23Z 置信度 0.70
• Edge Inference with Fully Differentiable Quantized Mixed Precision Neural Networks
  crossref Clemens J S Schaefer, Siddharth Joshi, Shan Li, Raul Blazquez 2024-04-09T17:36:09Z 置信度 0.70
• Quantifying Carbon Emissions of Machine Learning Inference Models Running on Edge IoT Devices
  crossref Aqsa Bano Kaim Khani, Sam Amiri, Luciano Ost 2026-07-14T19:39:06Z 置信度 0.70
• Context-dependent correlations mislead transcriptomic network inference in bulk and single-cell data
  Abstract Background Correlation is the dominant input to co-expression module discovery and miRNA-target inference. Both rely on an implicit assumption: a Pearson coefficient pooled across heterogeneous samples, whether tissues, cancer types, or cell types, es…
  crossref Amir Asiaee, Polina Bombina, Reginald L. McGee, Jake Reed 等 2026-06-29T20:15:21Z 置信度 0.70
• Architecture for Enabling Edge Inference via Model Transfer from Cloud Domain in a Kubernetes Environment
  The current approaches for energy consumption optimisation in buildings are mainly reactive or focus on scheduling of daily/weekly operation modes in heating. Machine Learning (ML)-based advanced control methods have been demonstrated to improve energy efficie…
  crossref Pekka Pääkkönen, Daniel Pakkala, Jussi Kiljander, Roope Sarala 2020-12-29T19:55:25Z 置信度 0.70
• A Reality Check on Inference at Mobile Networks Edge
  crossref Alejandro Cartas, Martin Kocour, Aravindh Raman, Ilias Leontiadis 等 2019-03-20T11:51:28Z 置信度 0.70
• Quantization at the Edge: Evaluating Inference Performance and Quality for SLM Driven Conversational Agents in Virtual Worlds
  crossref Louis Nisiotis, Nikita Markov 2026-08-20T19:04:54Z 置信度 0.70
• Live Demonstration: Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge
  crossref Corey Lammie, Mostafa Rahimi Azghadi 2020-09-29T13:22:27Z 置信度 0.70
• Oaci: Online Adaptive Collaborative Inference Among Edge Devices Under Resource-Constrained Conditions
  crossref Chao Yang, Jie Li, Enran Xie, Yuxing Liu 等 2025-09-26T17:34:55Z 置信度 0.70
• Intelligent Multi-Level Parking Management using Computer Vision, Edge Inference, and Reinforcement Learning for Slot Assignment
  The rapid expansion of urban transportation systems has intensified the demand for efficient and intelligent parking management solutions. Conventional parking approaches, which primarily depend on manual supervision or static sensor-based mechanisms, often fa…
  crossref Saravanan O, Harikarthick G 2026-06-03T10:30:37Z 置信度 0.70
• Communication resource allocation and multi-DNN inference optimization in edge computing-aided video analytics
  crossref Weiyang Qian, Rodolfo W.L. Coutinho, Azzedine Boukerche 2026-06-22T15:49:36Z 置信度 0.70
• Uncertainty-Gated Split Inference with Online Threshold Adaptation for Edge-IoT Under Dynamic Networks
  crossref Ali Asghari, Delaram Hosseinalizadeh 2026-08-18T19:14:10Z 置信度 0.70
• Efficient Unaligned Memory Access of Tightly Packed Weights for Deep Neural Network Inference on Edge Devices
  crossref Ciprian Seiculescu 2022-01-06T20:35:08Z 置信度 0.70
• Low- and Mixed-Precision Inference Accelerators
  crossref Maarten J. Molendijk, Floran A. M. de Putter, Henk Corporaal 2023-09-30T09:01:55Z 置信度 0.70
• Block-edge reduction in MPEG-1 coded images using statistical inference
  crossref S. Suthaharan 2002-11-22T18:04:31Z 置信度 0.70
• Privacy-Aware Adaptive Model Splitting for Device-Edge Co Inference
  crossref Guanwu Jiang, Shujun Han, Xiaodong Xu, Xiaofeng Tao 2024-03-21T17:52:58Z 置信度 0.70
• Evaluation of Membership Inference Attack Against Federated Learning With Differential Privacy on Edge Devices
  crossref Rei Ueda, Tsunato Nakai, Kota Yoshida, Takeshi Fujino 2023-11-16T18:52:44Z 置信度 0.70
• An Implementation of Secure Split Inference for Large Language Models on Resource-Constrained Edge Devices
  crossref Nada Hameed, Abu Kamruzzaman 2026-04-16T19:50:24Z 置信度 0.70
• Enabling Collaborative and Green Generative AI Inference in Edge Networks
  crossref Meng Tian, Zhicheng Liu, Chao Qiu, Xiaofei Wang 等 2025-03-11T17:30:35Z 置信度 0.70
• MACA: Memory-aware convolution accelerating for CNN inference on edge devices
  crossref Chaoxiong Yi, Songlei Jian, Yusong Tan, Yusen Zhang 2024-07-10T17:21:49Z 置信度 0.70
• Failure-Resilient ML Inference at the Edge through Graceful Service Degradation
  crossref Walid A. Hanafy, Li Wu, Tarek Abdelzaher, Suhas Diggavi 等 2023-12-25T19:37:01Z 置信度 0.70
• Optimal Input-Dependent Edge-Cloud Partitioning for RNN Inference
  crossref Daniele Jahier Pagliari, Roberta Chiaro, Yukai Chen, Enrico Macii 等 2020-01-23T22:15:31Z 置信度 0.70
• Energy-Efficient Edge Inference on Multi-Channel Streaming Data in 28nm HKMG FeFET Technology
  crossref S. Dutta, W. Chakraborty, J. Gomez, K. Ni 等 2019-07-26T00:25:02Z 置信度 0.70
• Facility-Location-based Model Partitioning for Efficient Inference in Edge Intelligence
  crossref Wenyun Ma, Chenshan Ren, Chunhui Ai 2026-07-02T19:42:44Z 置信度 0.70
• Adaptive Workload Distribution for Accuracy-aware DNN Inference on Collaborative Edge Platforms
  crossref Zain Taufique, Antonio Miele, Pasi Liljeberg, Anil Kanduri 2024-03-25T19:06:53Z 置信度 0.70
• Closing the Loop: Link-Aware Dataset Generation and Edge Learning in UAV-Based Inference Aerial Platforms
  crossref Andrea Caruso, Christian Grasso, Giovanni Schembra 2026-07-16T21:48:13Z 置信度 0.70
• A Simple Hybrid Filter Pruning for Efficient Edge Inference
  crossref S. H. Shabbeer Basha, Sheethal N Gowda, Jayachandra Dakala 2022-04-27T19:50:34Z 置信度 0.70
• Portable Neural Inference via WebAssembly on Resource-Constrained Edge Devices: A Case Study on ESP32-CAM
  crossref Rafael Costa Braga, Romulo Gonçalves Lins 2025-11-27T18:54:39Z 置信度 0.70
• SPICE: Structured Pruning for Inference on Constrained Edge Devices
  crossref Subhransu Das, Jiaming Cheng, Aniruddha Rakshit, Brijesh Soni 等 2026-02-04T20:45:15Z 置信度 0.70
• TinyML Implementation of CNN-Based Gait Analysis for Low-Cost Motorized Prosthetics: A Proof-of-Concept
  Real-time gait analysis is essential for the development of responsive and reliable motorized prosthetics. Deploying advanced deep learning models on resource-constrained embedded systems, however, remains a major challenge. This proof-of-concept study present…
  crossref João Vitor Y. B. Yamashita, João Paulo R. R. Leite, Jeremias B. Machado 2025-10-31T03:33:07Z 置信度 0.70
• A Delta Recurrent Neural Network Over TinyML Framework for Arithmetic Coding on the Edge
  crossref Bowei Shan, Yan Xia 2025-06-23T13:27:05Z 置信度 0.70
• TinyML Model for Solar Cell Defect Classification Based on Electroluminescence Images
  crossref S. Boubaker, C. Moussaoui, Adel Mellit, M. Benghanem 2025-03-19T20:33:11Z 置信度 0.70
• Securing Insulin Pumps Against Malicious Injections: A TinyML-Based Anomaly Detection Approach
  crossref Khadija Tlemçani, Kebira Azbeg, Leila Fetjah, Ouail Ouchetto 等 2025-10-07T07:54:59Z 置信度 0.70
• TinyML-enabled structural health monitoring for real-time anomaly detection in civil infrastructure
  crossref Asma Alshuhail, Hanan Abdullah Mengash, Meshari H. Alanazi, Muhammad Kashif Saeed 等 2025-09-05T21:26:37Z 置信度 0.70
• Time Series-Based Electrical Device Classification on Edge with TinyML
  crossref Tolga Reis, Ahmet Teoman Naskali 2025-10-01T00:16:22Z 置信度 0.70
• Special Session - Intermittent TinyML: Powering Sustainable Deep Intelligence Without Batteries
  crossref Hashan Roshantha Mendis, Kasim Sinan Yildirim, Marco Zimmerling, Luca Mottola 等 2025-12-05T17:59:20Z 置信度 0.70
• Optimizing TinyML Models for Real-Time Environmental Monitoring: A Comparative Study of Compression Techniques
  crossref Shubneet, Anushka Raj Yadav, Partha Chanda, Shiyabrinta Bhowmik 等 2025-10-18T15:03:05Z 置信度 0.70
• A LOW POWER DYNAMIC BITWIDTH-ADAPTIVE MULTIPLY ACCUMULATE UNIT FOR TINYML ACCELERATORS
  With the increasing demand for the deployment of machine learning models on energy-efficient and low-latency devices, TinyML stands out as an efficient solution for enabling intelligence on edge-constrained devices. TinyML workloads often need energy efficient…
  crossref Shyam Perika, Boddu Ajay, Sumanto Kar 2025-09-26T09:13:58Z 置信度 0.70
• Addressing Limitations of TinyML Approaches for AI-Enabled Ambient Intelligence
  crossref Antoine Bonneau, Frédéric Le Mouël, Fabien Mieyeville 2024-12-31T22:59:59Z 置信度 0.70
• TinyML: Small Models Making a Big Impact
  crossref Ismail Lamaakal, Chaymae Yahyati, Yassine Maleh, Khalid El Makkaoui 等 2026-05-06T22:07:05Z 置信度 0.70
• Development and Prototyping of a Speech-To-Text (STT) Model and Lip Recognition Software for Tiny Machine Learning (TinyML) Systems
  crossref Logan Wong Duran, Mithil Darur, Kok Zuea Tang 2025-05-03T04:57:44Z 置信度 0.70
• Safeguarding IoT consumer devices: Deep learning with TinyML driven real-time anomaly detection for predictive maintenance
  crossref Iyad Katib, Emad Albassam, Sanaa A. Sharaf, Mahmoud Ragab 2025-01-27T05:23:42Z 置信度 0.70
• Optimizing TinyML Models for Bird Call Recognition via Multi-objective Bayesian Search and Knowledge Distillation
  crossref Agnivo Ghosh, Soumen Garai, Suman Samui 2026-04-20T11:51:28Z 置信度 0.70
• StreamNet++: Memory-Efficient Streaming TinyML Model Compilation on Microcontrollers
  The rapid growth of on-device artificial intelligence increases the importance of TinyML inference applications. However, the stringent tiny memory space on the microcontroller unit (MCU) raises the grand challenge when deploying deep neural network (DNN) mode…
  crossref Chen-Fong Hsu, Hong-Sheng Zheng, Yu-Yuan Liu, Tsung Tai Yeh 2024-11-29T09:29:47Z 置信度 0.70
• TEDA-forecasting: an unsupervised tinyML incremental learning approach for outlier processing and forecasting
  crossref Pedro Andrade, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa 等 2025-07-02T02:46:47Z 置信度 0.70
• TinyMetaFed: Efficient Federated Meta-learning for TinyML
  crossref Haoyu Ren, Xue Li, Darko Anicic, Thomas A. Runkler 2024-12-31T23:00:33Z 置信度 0.70
• Data Stream Processing for Resource-Constrained TinyML Systems
  crossref Tobiasz Puslecki, Krzysztof Walkowiak 2026-05-09T22:07:42Z 置信度 0.70
• OdorNet: A lightweight odor recognition method for TinyML in handheld electronic noses using spatiotemporal pseudo-images
  crossref Xin Weng, Jun Fu, Jiayu Ye, Ruifen Hu 等 2025-07-24T15:09:14Z 置信度 0.70
• TinyML Approach for Pre-fall Motion Pattern Detection in Older Adults
  crossref Jefferson Sarmiento-Rojas, Angela Maria Torres-Lara, Pedro Antonio-Aya Parra, Jonnier Sebastián Jaramillo-Isaza 等 2025-10-15T11:57:16Z 置信度 0.70
• An IoT-Based Multimodal Wearable Framework for Real-Time Epileptic Seizures Detection Using TinyML
  crossref Yassmine Ben Dhiab, Moez Hizem, Nader Karmous, Mohamed Ould-Elhassen Aoueileyine 等 2025-04-10T14:18:32Z 置信度 0.70
• TinyML-Based Intrusion Detection System for Handling Class Imbalance in IoT-Edge Domain Using Siamese Neural Network on MCU
  crossref Pietro Fusco, Alberto Montefusco, Gennaro Pio Rimoli, Francesco Palmieri 等 2025-04-07T02:37:18Z 置信度 0.70
• Nephrology Review
  Scott L. Larson, RPh, PharmDThe questions and answers in this chapter are available to subscribers as part of the Oxford eLearning platform. To access the questions, follow the link below, or go to http://oxford-elearning.oup.com/bookshttp://oxford-elearning.o…
  crossref 2012-07-28T10:20:37Z 置信度 0.70
• Cardiology Review
  Extract Cardiology Pharmacy Review Narith N. Ou, RPh, PharmD, Jeffrey J. Armon, RPh, PharmD Drugs Commonly Used for Cardiac Resuscitation Drugs Commonly Used in Cardiology Selected Important Cardiac Drug Interactions ... Questions and Answers Questions Multipl…
  crossref 2012-07-28T10:20:37Z 置信度 0.70
• Neurology Review
  crossref 2012-07-28T10:20:37Z 置信度 0.70
• Gastroenterology Review
  crossref 2012-07-28T10:20:37Z 置信度 0.70
• Optimizing battery life: a TinyML approach to lithium-ion battery health monitoring
  <span lang="EN-US">Electrical vehicles (EVs) are crucial nowadays due to their reduction in greenhouse gas emissions, decreasing dependence on remnant fuels, and improving air quality. For EVs, the battery is the heart that determines range, performance,…
  crossref Kamaraj Lalitha Nisha, Vasanth Pradeep, Padmanabhan Puthiyaveedu Krishnankutty Nair, Sreelakshmi Pillai 等 2025-10-14T13:37:56Z 置信度 0.70
• Ultra-Low Power Sensor Data Processing in Smart Agriculture Using Attention-Optimized TinyML Models for Edge Microcontrollers
  crossref Jaafar Hamza Kadhum, Ahmed Dheyaa Radhi, Laith S. Ismail, Mohammed Ghaleb Waheed 等 2025-12-19T18:56:15Z 置信度 0.70
• TinyML-Powered Deep Learning for Real-Time Stress Detection and Health Monitoring
  crossref Merouane Mouadili, El Mokhtar En-Naimi, Mohamed Kouissi 2025-10-26T17:01:43Z 置信度 0.70
• TinyML-Based Approach for Dynamic Transmission Power in LoRaWAN Network
  crossref Muhammad Ali Lodhi, Lei Wang, Khalid Ibrahim Qureshi, Khalid Mahmood 2025-02-28T19:48:46Z 置信度 0.70
• TinyML and Federated Learning for Resource-Constrained Medical Devices
  crossref Pietro Fusco, Gennaro Pio Rimoli, Massimo Ficco 2025-01-22T01:53:05Z 置信度 0.70
• Implementing TinyML in Internet of Things devices: A systematic literature review
  crossref Andrés Felipe Solis Pino, Daniel Steven Moran Pizarro, Pablo H. Ruiz, Vanessa Agredo-Delgado 等 2026-01-10T00:38:10Z 置信度 0.70
• SmartBioGas-PIoT: Physics-informed edge AI and TinyML for real-time monitoring and methane rate prediction in anaerobic digesters
  crossref Faiyaz Khan Sami, Zakia Sultana Nisa, Md. Hasan Imam Bijoy, Fizar Ahmed 等 2026-04-21T23:48:08Z 置信度 0.70
• TyBox: An Automatic Design and Code Generation Toolbox for TinyML Incremental On-Device Learning
  Incremental on-device learning is one of the most relevant and interesting challenges in the field of Tiny Machine Learning (TinyML). Indeed, differently from traditional TinyML solutions where the training is typically carried out on the Cloud and inference o…
  crossref Massimo Pavan, Eugeniu Ostrovan, Armando Caltabiano, Manuel Roveri 2023-06-17T09:12:46Z 置信度 0.70
• Design and Performance Evaluation of an Ultralow-Power Smart IoT Device With Embedded TinyML for Asset Activity Monitoring
  crossref Marco Giordano, Nicolas Baumann, Michele Crabolu, Raphael Fischer 等 2022-04-15T15:23:29Z 置信度 0.70
• Development of Smart Underground Drainage Leak Detection and Localization Using Acoustic and Flow Sensing with TINYML and IOT
  Abstract -Underground pipeline leakage leads to significant water loss, infrastructure damage, and economic impact, necessitating efficient detection and localization methods. This paper presents a smart leak detection system that integrates acoustic sensing, …
  crossref Mohamed Islah K I, Elezabeth Skaria, Kavitha Issac, Aby Krishnan U 等 2026-03-29T11:06:41Z 置信度 0.70
• Elements of TinyML on Constrained Resource Hardware
  crossref Vasileios Tsoukas, Anargyros Gkogkidis, Athanasios Kakarountas 2022-07-27T12:49:18Z 置信度 0.70
• Comparative Analysis and Implementation of Energy-Quality Scalable Multiply-Accumulate Architectures for TinyML Applications
  crossref Kenn Danielle C. Pelayo, Anastacia B. Alvarez, Adelson N. Chua, Fredrick Angelo R. Galapon 等 2025-01-28T18:32:08Z 置信度 0.70
• A 340- μ W TinyML Using LUT-Based Reservoir Computing on Low-Cost FPGAs
  crossref Kanta Yoshioka, Hakaru Tamukoh 2025-10-16T17:37:45Z 置信度 0.70
• Power Efficient Non-Mechanical Weather Station: Harnessing TinyML for Rainfall Classification and Environmental Sensing
  crossref Dennis Agyemanh Nana Gookyi, Fortunatus Aabangbio Wulnye, Roger Kwao Ahiadormey, Michael Wilson 等 2025-01-30T19:09:50Z 置信度 0.70
• Proof of Concept: A TinyML-Based Image Classifier for Detecting Microplastics and Waste in Simulated Marine Environments
  crossref Ciara Mendez-Cruz, Camilo Silva-Cuzqui, Luz Vasco-Aredondo, Renzo Chan-Rios 等 2025-01-14T19:42:17Z 置信度 0.70
• Developing a multi-label tinyML machine learning model for an active and optimized greenhouse microclimate control from multivariate sensed data
  crossref Ilham Ihoume, Rachid Tadili, Nora Arbaoui, Mohamed Benchrifa 等 2022-09-05T19:56:28Z 置信度 0.70
• TinyML Benchmark: Executing Fully Connected Neural Networks on Commodity Microcontrollers
  crossref Bharath Sudharsan, Simone Salerno, Duc-Duy Nguyen, Muhammad Yahya 等 2021-11-09T20:44:20Z 置信度 0.70
• TinyML-Based Human and Animal Movement Detection in Agriculture Fields in India
  crossref V. Viswanatha, A. C. Ramachandra, Puneet T. Hegde, Vivek Hegde 等 2024-01-06T13:02:23Z 置信度 0.70
• A 1036 TOp/s/W, 12.2 mW, 2.72 μJ/Inference All Digital TNN Accelerator in 22 nm FDX Technology for TinyML Applications
  crossref Moritz Scherer, Alfio Di Mauro, Georg Rutishauser, Tim Fischer 等 2022-05-16T20:45:15Z 置信度 0.70
• TinyML-Based Gait Recognition for User Detection on an STM32L4 IoT Node
  crossref Hateem Hassan, M. Abdullah, Muhammad Zunnurain Hussain, Muhammad Zulkifl Hasan 等 2024-06-10T17:19:31Z 置信度 0.70
• A Model-Specific End-to-End Design Methodology for Resource-Constrained TinyML Hardware
  crossref Yanchi Dong, Tianyu Jia, Kaixuan Du, Yiqi Jing 等 2023-09-15T17:31:31Z 置信度 0.70
• A 0.8 mW TinyML-Based PDM-to-PCM Conversion for In-Sensor KWS Applications
  crossref Paola Vitolo, Rosalba Liguori, Luigi Di Benedetto, Alfredo Rubino 等 2023-02-27T20:02:53Z 置信度 0.70
• Integrating Analog PIR Sensor Telemetry with TinyML Inference for On-The-Edge Classification of Moving Objects
  crossref Ritha M. Umutoni, Marvin Ogore, Damien Hanyurwimfura, Jimmy Nsenga 2023-07-29T16:01:54Z 置信度 0.70
• An Unsupervised TinyML Approach Applied for Pavement Anomalies Detection Under the Internet of Intelligent Vehicles
  crossref Pedro Andrade, Ivanovitch Silva, Gabriel Signoretti, Marianne Silva 等 2021-07-27T21:09:31Z 置信度 0.70
• A New NN-Based Approach to In-Sensor PDM-to-PCM Conversion for Ultra TinyML KWS
  crossref Paola Vitolo, Rosalba Liguori, Luigi Di Benedetto, Alfredo Rubino 等 2022-11-24T16:58:24Z 置信度 0.70