{"total":17,"rows":[{"id":"2101.09671","title":"Pruning and Quantization for Deep Neural Network Acceleration: A Survey","created":"2021-01-24","cited_by_count":263,"area":null},{"id":"2108.11663","title":"Convolutional Neural Networks Demystified: A Matched Filtering Perspective Based Tutorial","created":"2021-08-26","cited_by_count":6,"area":null},{"id":"2307.04049","title":"Parallel Algorithms Align with Neural Execution","created":"2023-07-08","cited_by_count":6,"area":null},{"id":"2201.09167","title":"Mixed X-Ray Image Separation for Artworks with Concealed Designs","created":"2022-01-23","cited_by_count":4,"area":null},{"id":"2209.13500","title":"Dense-TNT: Efficient Vehicle Type Classification Neural Network Using Satellite Imagery","created":"2022-09-27","cited_by_count":3,"area":null},{"id":"2108.13055","title":"Efficient Visual Recognition with Deep Neural Networks: A Survey on Recent Advances and New Directions","created":"2021-08-30","cited_by_count":2,"area":null},{"id":"2106.06688","title":"BRAIN2DEPTH: Lightweight CNN Model for Classification of Cognitive States from EEG Recordings","created":"2021-06-12","cited_by_count":1,"area":null},{"id":"2107.09095","title":"A New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks","created":"2021-07-19","cited_by_count":1,"area":null},{"id":"2306.04240","title":"T-ADAF: Adaptive Data Augmentation Framework for Image Classification Network based on Tensor T-product Operator","created":"2023-06-07","cited_by_count":1,"area":null},{"id":"2505.13461","title":"FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review","created":"2025-05-04","cited_by_count":1,"area":null},{"id":"2107.09101","title":"Accelerating deep neural networks for efficient scene understanding in automotive cyber-physical systems","created":"2021-07-19","cited_by_count":0,"area":null},{"id":"2109.05397","title":"Challenges and Solutions in DeepFakes","created":"2021-09-12","cited_by_count":0,"area":null},{"id":"2209.09168","title":"Application of Neural Network in the Prediction of NOx Emissions from Degrading Gas Turbine","created":"2022-09-19","cited_by_count":0,"area":null},{"id":"2304.04005","title":"A new transformation for embedded convolutional neural network approach toward real-time servo motor overload fault-detection","created":"2023-04-08","cited_by_count":0,"area":null},{"id":"2305.09407","title":"A Novel Strategy for Improving Robustness in Computer Vision Manufacturing Defect Detection","created":"2023-05-16","cited_by_count":0,"area":null},{"id":"2406.00290","title":"Phasor-Driven Acceleration for FFT-based CNNs","created":"2024-06-01","cited_by_count":0,"area":null},{"id":"2601.01254","title":"Entity-Aware and Secure Query Optimization in Database Using Named Entity Recognition","created":"2026-01-03","cited_by_count":0,"area":null}],"next_cursor":null}