Results 61 to 70 of about 22,886 (195)
NeurAll: Towards a Unified Visual Perception Model for Automated Driving
Convolutional Neural Networks (CNNs) are successfully used for the important automotive visual perception tasks including object recognition, motion and depth estimation, visual SLAM, etc.
Chennupati, Sumanth +6 more
core
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source
Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang +9 more
wiley +1 more source
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson +3 more
wiley +1 more source
Device‐Level Implementation of Reservoir Computing With Memristors
Reservoir computing (RC) is an emerging computing scheme that employs a reservoir and a single readout layer, which can be actualized in the nanoscale with memristors. As a comprehensive overview, the principles of RC and the switching mechanisms of memristors are discussed, followed by actual demonstrations of memristor‐based RC and the remaining ...
Sunbeom Park, Hyojung Kim, Ho Won Jang
wiley +1 more source
EMG‐Driven Telemetry and Inference System for Fish: Pose Reconstruction and Flow Sensing
This work introduces an electromyography (EMG)‐driven telemetry framework that reconstructs body pose and infers hydrodynamic conditions in freely swimming fish. A custom 16‐channel archival system records intramuscular EMG, enabling deep‐learning models to decode joint kinematics, classify flow regimes, and reveal channel‐efficient sensing strategies.
Rahdar Hussain Afridi +7 more
wiley +1 more source
Intelligent Operator‐Independent Flexibility in Robotic Non‐Destructive Evaluation
Non‐destructive evaluation of high‐value components remains a manufacturing bottleneck due to rigid robotic calibration and fixturing. This study presents a flexible, adaptable system integrating 3D vision and force‐position control with a collaborative KUKA LBR robot. The geometry‐agnostic system enables pose‐independent ultrasonic inspection, detects
Amine Hifi +11 more
wiley +1 more source
A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan +6 more
wiley +1 more source
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source

