-
101
-
102
<italic>WhiteDwarf</italic>: A Holistic Co-Design Approach to Ultra-Compact Neural Inference Acceleration
Published 2025-01-01“…The fabricated 40-nm CMOS chip, aimed at high inference accuracy and power efficiency, achieves 12.24 TFLOPS/W at 99% weight sparsity.…”
Get full text
Article -
103
Neural architecture codesign for fast physics applications
Published 2025-01-01“…We exceed performance on various tasks and show further speedup through model compression techniques such as quantization-aware-training and neural network pruning. …”
Get full text
Article -
104
-
105
Filter Implementation for Power-Efficient Chromatic Dispersion Compensation
Published 2018-01-01“…Chromatic dispersion (CD) compensation in coherent fiber-optic systems represents a very significant DSP block in terms of power dissipation. Since spectrally efficient coherent systems are expected to find a wider deployment in systems shorter than long haul, it becomes relevant to investigate filter implementation aspects of CD compensation in the context of systems with low-to-moderate amounts of accumulated dispersion. …”
Get full text
Article -
106
-
107
Collaborative Learning for Task-Oriented Semantic Communications: Overcoming Data Mismatch Between Transceivers
Published 2025-01-01“…Task-oriented semantic communication (ToSC) enhances efficiency and performance by leveraging task-specific data representations and end-to-end learning, which are more compact and effective than traditional reconstruction-oriented methods. …”
Get full text
Article -
108
Optimized Ensemble Deep Learning for Real-Time Intrusion Detection on Resource-Constrained Raspberry Pi Devices
Published 2025-01-01“…The proposed system maintains high detection performance with accuracy of 97.3% across all test scenarios, while efficiently leveraging multi-core processing with peak CPU usage reaching 111.8%. …”
Get full text
Article -
109
An Intelligent Smart Dynamic Feature Analysis Based Approach by Utilizing Deep Learning to Improve the Breast Cancer Detection
Published 2025-01-01“…The model was also trained using Quantization aware training (QAT) to enable efficient deployment on low-resource devices without significant performance degradation. …”
Get full text
Article -
110
A survey of model compression techniques: past, present, and future
Published 2025-03-01“…To meet the urgent demand for efficient deployment, we delve into several compression methods—such as quantization, pruning, low-rank decomposition, and knowledge distillation—emphasizing their fundamental principles, recent advancements, and innovative strategies. …”
Get full text
Article -
111
GMT: Gzip-based Memory-efficient Time-series classification
Published 2025-04-01“…We introduce GMT, a memory-efficient parameter-free classifier that uses gzip compressor and k-nearest neighbors (kNN) for classifying multi-channel time-series data. …”
Get full text
Article -
112
An Efficient Architecture for Edge AI Federated Learning With Homomorphic Encryption
Published 2025-01-01“…With the rapid growth of edge AI applications, there is an increasing demand for federated learning (FL) frameworks that are both efficient and privacy-preserving. This work introduces a robust approach that leverages homomorphic encryption (HE) to ensure data confidentiality during decentralized training. …”
Get full text
Article -
113
Energy-Efficient Deep Learning for Cloud Detection Onboard Nanosatellite
Published 2025-01-01“…The customized SegNet architecture, tailored with minimal kernels and layers, achieved an accuracy of 93.50%, effectively balancing performance and computational efficiency. Quantization further optimized energy consumption, achieving a reduction of 82.2% at 280 MHz. …”
Get full text
Article -
114
Efficient Real-Time Isotope Identification on SoC FPGA
Published 2025-06-01“…Efficient real-time isotope identification is a critical challenge in nuclear spectroscopy, with important applications such as radiation monitoring, nuclear waste management, and medical imaging. …”
Get full text
Article -
115
An all integer-based spiking neural network with dynamic threshold adaptation
Published 2024-12-01“…Due to this all integer-based quantization process, the required computational operations are significantly reduced, potentially providing a substantial energy efficiency advantage for numerous edge computing applications.…”
Get full text
Article -
116
Sports activity in functional systems theory
Published 2016-09-01“…The article demonstrates the efficiency of the systemic approach to analyze athletes' reserve capacity increase resulting from fatigue and physical performance decrease resulting from overfatigue.…”
Get full text
Article -
117
Deep Learning Model Compression and Hardware Acceleration for High-Performance Foreign Material Detection on Poultry Meat Using NIR Hyperspectral Imaging
Published 2025-02-01“…Ensuring the safety and quality of poultry products requires efficient detection and removal of foreign materials during processing. …”
Get full text
Article -
118
Comparative analysis of model compression techniques for achieving carbon efficient AI
Published 2025-07-01“…We also compared the energy efficiency of these compressed models against inherently carbon-efficient transformer models, such as TinyBERT and MobileBERT. …”
Get full text
Article -
119
An efficient post-processing adaptive filtering technique to rectifying the flickering effects.
Published 2021-01-01“…This paper focuses on an efficient pre-and post-processing technique (PP-AFT) to address and rectify the problems of quantization error, ringing, blocking artifact, and flickering effect, which significantly degrade the visual quality of video frames. …”
Get full text
Article -
120
Feature-Based Federated Transfer Learning: Communication Efficiency, Robustness and Privacy
Published 2024-01-01“…In this paper, we propose feature-based federated transfer learning as a novel approach to improve communication efficiency by reducing the uplink payload by multiple orders of magnitude compared to that of existing approaches in federated learning and federated transfer learning. …”
Get full text
Article