Results 51 to 60 of about 693,698 (310)

EffNet-SVM: A Hybrid Model for Diabetic Retinopathy Classification Using Retinal Fundus Images

IEEE Access
The manual diagnosis of diabetic retinopathy (DR) is often invasive, time-consuming, expensive, and prone to human error. Additionally, it can be subjective, depending on the clinician’s professional experience.
K. V. Naveen, B. N. Anoop, K. S. Siju, Mithun Kumar Kar, Vipin Venugopal   +4 more
doaj   +1 more source

COVID-19 Image Classification: A Comparative Performance Analysis of Hand-Crafted vs. Deep Features

Computation
This study investigates techniques for medical image classification, specifically focusing on COVID-19 scans obtained through computer tomography (CT).
Sadiq Alinsaif
doaj   +1 more source

A Novel Algorithm Based on a Common Subspace Fusion for Visual Object Tracking

IEEE Access, 2022
Recent methods for visual tracking exploit a multitude of information obtained from combinations of handcrafted and/or deep features. However, the response maps derived from these feature combinations are often fused using simple strategies such as ...
Sajid Javed, Arif Mahmood, Ihsan Ullah, Thierry Bouwmans, Majid Khonji, Jorge Manuel Miranda Dias, Naoufel Werghi   +6 more
doaj   +1 more source

Deep Learning Application to Ensemble Learning—The Simple, but Effective, Approach to Sentiment Classifying

Applied Sciences, 2019
Sentiment analysis is an active research area in natural language processing. The task aims at identifying, extracting, and classifying sentiments from user texts in post blogs, product reviews, or social networks.
Thien Khai Tran, Tuoi Thi Phan
doaj   +1 more source

iAceS-Deep: Sequence-Based Identification of Acetyl Serine Sites in Proteins Using PseAAC and Deep Neural Representations

IEEE Access, 2022
In the biological systems, Acetylation is a crucial post-translational modification, prevalent in various physiological functions and pathological conditions like carcinoma and malignancies.
Sheraz Naseer, Suliman Mohamed Fati, Amgad Muneer, Rao Faizan Ali   +3 more
doaj   +1 more source

A Bibliometric Analysis of Publications in Uremic Toxins From 1991 to 2024

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Uremic toxins are a growing area of research in nephrology, with significant implications in the progression and treatment of chronic kidney disease (CKD) and the management of end‐stage kidney disease (ESKD). This bibliometric analysis aims to evaluate the global research trends, key contributors, and the impact of publications in ...
Yuh‐Shan Ho, Karim M. Soliman, Wisit Cheungpasitporn, Wannasit Wathanavasin, Ahmed Daoud, Ahmed I. Kamal, Balázs Szamosfalvi, Tibor Fülöp   +7 more
wiley   +1 more source

Learning Deep Features for Scene Recognition using Places Database [PDF]

, 2014
Scene recognition is one of the hallmark tasks of computer vision, allowing definition of a context for object recognition. Whereas the tremendous recent progress in object recognition tasks is due to the availability of large datasets like ImageNet and ...
Antonio Torralba, Aude Oliva, Torralba, Antonio, Xiao, Jianxiong, Bolei Zhou, Jianxiong Xiao, Agata Lapedriza, Lapedriza, Agata, Lapedriza Garcia, Agata, Zhou, Bolei, Oliva, Aude   +10 more
core  

Experience With Performing Rheocarna Therapy via the Single‐Needle Method for Treatment of Chronic Limb‐Threatening Ischemia

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Introduction This study investigated the safety and efficacy of single‐needle Rheocarna therapy for chronic limb‐threatening ischemia (CLTI) with wounds. Methods Six patients with CLTI involving ulcers unresponsive to revascularization underwent single‐needle Rheocarna treatment.
Yasutaka Yamauchi, Rie Tanaka, Reona Kawahira, Shingo Nabeta, Kouhei Naoi, Kazuhito Kitajima, Akira Wada, Tomonari Takagi, Norihiko Ohura, Akira Miyamoto   +9 more
wiley   +1 more source

Fused-Deep-Features Based Grape Leaf Disease Diagnosis

, 2021
Rapid and accurate grape leaf disease diagnosis is of great significance to its yield and quality of grape. In this paper, aiming at the identification of grape leaf diseases, a fast and accurate detection method based on fused deep features, extracted ...
Yun Peng, Shengyi Zhao, Jizhan Liu
core   +1 more source

Human-Assisted vs. Deep Learning Feature Extraction: An Evaluation of ECG Features Extraction Methods for Arrhythmia Classification Using Machine Learning

Applied Sciences, 2022
The success of arrhythmia classification tasks with Machine Learning (ML) algorithms is based on the handcrafting extraction of features from Electrocardiography (ECG) signals.
Larissa Montenegro, Mariana Abreu, Ana Fred, Jose M. Machado   +3 more
doaj   +1 more source