Results 41 to 50 of about 19,743 (267)

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

open access: yesAdvanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho   +6 more
wiley   +1 more source

Hyperspectral Imaging for Enhanced Skin Cancer Classification Using Machine Learning

open access: yesBioengineering
Objective: The classification of skin cancer is very helpful in its early diagnosis and treatment, considering the complexity involved in differentiating AK from BCC and SK.
Teng-Li Lin   +5 more
doaj   +1 more source

People Counting and Positioning Using Low‐Resolution Infrared Images for FeFET‐Based In‐Memory Computing

open access: yesAdvanced Electronic Materials, EarlyView.
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar   +9 more
wiley   +1 more source

Empowering and conquering infirmity of visually impaired using AI‐technology equipped with object detection and real‐time voice feedback system in healthcare application

open access: yesCAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract The Internet of Things is emerging as a crucial technology in aiding humans and making their lives easier. Among the human population, a large percentage of people suffer from disabilities resulting in challenges in everyday life particularly people with visual disabilities.
Hania Tarik   +8 more
wiley   +1 more source

Hybrid Backbone-Based Deep Learning Model for Early Detection of Forest Fire Smoke

open access: yesApplied Sciences
Accurate forest fire detection is critical for the timely intervention and mitigation of environmental disasters. It is very important to intervene in forest fires before major damage occurs by using smoke data.
Gökalp Çınarer
doaj   +1 more source

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

open access: yesAdvanced Intelligent Discovery, EarlyView.
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri   +6 more
wiley   +1 more source

GY-YOLO: ghost separable YOLO for pedestrian detection

open access: yesNeural Computing and Applications
Abstract In recent years, there has been impressive development in human detection. The main challenge in pedestrian detection is the training data. To assess detectors in crowd scenarios more effectively, a novel dataset in this study called the HEP dataset (Hybrid Egyptian Pedestrian dataset) is introduced. The HEP dataset is extensive, has
Ali M. Elhenidy   +3 more
openaire   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

From YOLO V1 to YOLO V11: comparative analysis of YOLO algorithm (review)

open access: yesInternational Journal of Electrical and Computer Engineering (IJECE)
Object detection in images or videos faces several challenges because the detection must be accurate, efficient and fast. The you only look once (YOLO) algorithm was invented to meet these criteria. But with the creation of several versions of this algorithm (from V1 to V11), it becomes difficult for researchers to choose the best one.
Imane Beqqali Hassani   +5 more
openaire   +1 more source

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

open access: yesAdvanced Intelligent Discovery, EarlyView.
AI‐based tools enable rapid characterization of bacterial ultrastructure in low‐dose cryogenic transmission electron microscopy. The envelope thickness tool quantifies membrane thickness and anisotropy. The flagella module analyzes filament morphology and detects cell‐flagella contacts.
Sita Sirisha Madugula   +10 more
wiley   +1 more source

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