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Data Pipelines For AI Agents: Building The Backbone Of Intelligent Automation
The infrastructure behind AI agents isn't static—it’s a living, evolving system. Designing effective data pipelines means ...
IEEE2d
Dynamic Semantic Compression for CNN Inference in Multi-Access Edge Computing: A Graph Reinforcement Learning-Based Autoencoder - IEEE Xplore
This paper studies the computational offloading of CNN inference in dynamic multi-access edge computing (MEC) networks. To address the uncertainties in communication time and edge servers’ available ...
IEEE2d
M-net: A Convolutional Neural Network for deep brain structure segmentation - IEEE Xplore
In this paper, we propose an end-to-end trainable Convolutional Neural Network (CNN) architecture called the M-net, for segmenting deep (human) brain structures from Magnetic Resonance Images (MRI). A ...
Semiconductor Engineering4d
Accelerator Architecture For In-Memory Computation of CNN Inferences Using Racetrack Memory
A new technical paper titled “Hardware-software co-exploration with racetrack memory based in-memory computing for CNN ...
IEEE5d
Multi-Stream 1D CNN for EEG Motor Imagery Classification of Limbs Activation - IEEE Xplore
In this paper, a novel multi-stream 1D Convolutional Neural Network (CNN) architecture is proposed. The input EEG signal is processed by four convolutional streams, which differ in the size of ...
IEEE5d
BEFNet: A Hybrid CNN-Mamba Architecture for Accurate Skin Lesion Image Segmentation - IEEE Xplore
Accurate image segmentation of skin lesions is crucial for the detection and treatment of skin cancer. Based on the modern state space model Mamba, a novel hybrid CNN-Mamba network (BEFNet) is ...
IEEE5d
Real time lane detection using CNN - IEEE Xplore
Road lane detection plays a crucial role in advancing autonomous driving technologies, enhancing vehicle safety, and contributing to intelligent transportation systems. This paper proposes a road lane ...
IEEE5d
A High-Throughput and Power-Efficient FPGA Implementation of YOLO CNN for Object Detection - IEEE Xplore
Convolutional neural networks (CNNs) require numerous computations and external memory accesses. Frequent accesses to off-chip memory cause slow processing and large power dissipation. For real-time ...