The bone marrow cell analysis is taken as the critical standard for diagnosing leukemia. However, owing to the diverse morphology of these bone marrow cells, a lot of patience along with extensive experience is requir...
详细信息
The proceedings contain 87 papers. The topics discussed include: head posture recognition based on Newton-Raphson method;valid activity acquisition and recognition with WIFI based on blind source separation;an online ...
ISBN:
(纸本)9781450387835
The proceedings contain 87 papers. The topics discussed include: head posture recognition based on Newton-Raphson method;valid activity acquisition and recognition with WIFI based on blind source separation;an online prediction and trajectory tracking method for human activity recognition;weakly supervised fine-grained image recognition based on multi-channel attention and object localization;a lightweight handwriting recognition system based on an improved convolutional neural network;a model for luggage re-identification based on the network ensemble;AMINN: attention-based multi-information neural network for emotion recognition;a modular lane detection method based on scene understanding;asymmetric convolution-based neural network for SAR ship detection from scratch;and modulation characteristics of coherent motion field for the moving vehicles.
Intuitionistic fuzzy set is a significance softcomputing tool for curbing fuzziness embedded in decision-making processes. To enhance the applicability of intuitionistic fuzzy sets in modelling practical real-life pr...
详细信息
Intuitionistic fuzzy set is a significance softcomputing tool for curbing fuzziness embedded in decision-making processes. To enhance the applicability of intuitionistic fuzzy sets in modelling practical real-life problems, various computing methods have been proposed like distance measures, similarity measures and correlation measures. This paper proposes an intuitionistic fuzzy statistical correlation algorithm with applications to patternrecognition and diagnostic processes. This novel method assesses the magnitude of relationship and indicates whether the intuitionistic fuzzy sets under consideration are correlated in either positive or negative sense. We substantiate the proposed technique with some theoretical results and numerically validate it to be superior in terms of accuracy and reliability in contrast to some hitherto techniques. Finally, we determine decision-making processes involving patternrecognition and diagnostic processes by using JAVA programming language to code the intuitionistic fuzzy statistical correlation measure.
The study explores the visualization and analysis of historical data for the NASDAQ Composite Index (^IXIC) using Tableau. It examines trends in daily closing prices and volume distribution and compares performance wi...
详细信息
Extraction of the local color texture has been one of the most desired and challenging research areas in face image recognition due to the ever-increasing use of color face images in numerous applications including bi...
详细信息
The proceedings contain 31 papers. The topics discussed include: efficient virtual network embedding with hierarchical and cooperative multi-agent reinforcement learning;testing neurofeedback system for studying cogni...
ISBN:
(纸本)9798350332391
The proceedings contain 31 papers. The topics discussed include: efficient virtual network embedding with hierarchical and cooperative multi-agent reinforcement learning;testing neurofeedback system for studying cognitive tests;a survey on human factors in cyberspace: a new dimension of privacy threats;user recognition based on gait pattern via smartwatch accelerometer in unrestricted environment;performing walk-through energy audits in smart homes;exploration of machine learning algorithms for development of intelligent intrusion detection systems;chaos-based secured modified strong recovery conditions for least support orthogonal matching pursuit in the noisy case;machine learning technique to monitor heartbeat using amalgamated data of multi-sensor stream;a metadata approach to classify domain-specific documents for event-based surveillance systems;a novel font color and compression text steganography technique;hybrid deep learning approach for nonfunctional software requirements classifications;and consensus MPC-based hierarchical control of islanded AC microgrid.
The proceedings contain 67 papers. The topics discussed include: an application of fuzzy geographically clustering for solving the cold-start problem in recommender systems;object tracking simulates babysitter vision ...
ISBN:
(纸本)9781479934003
The proceedings contain 67 papers. The topics discussed include: an application of fuzzy geographically clustering for solving the cold-start problem in recommender systems;object tracking simulates babysitter vision robot using GMM;a survey on hybridizing genetic algorithm with dynamic programming for solving the traveling salesman problem;stroke segmentation of online handwritten word using the busy zone concept;a note of liver cirrhosis classification on m-mode ultrasound images by higher-order local auto-correlation features;using motif information to improve anytime time series classification;a fast temporal median filter and its applications for background estimation in video surveillance;hiding data in audio using modified CPT scheme;interpolative reasoning approach to sparse general type-2 fuzzy rules based on the reduced grid representation;and a genetic-based approach for discovering pathways in protein-protein interaction networks.
In this paper, the noise is smoothed by the relative total variation model;the processed digital image is converted from the RGB color space to the CIE L ∗ a ∗ b ∗ color space, and the two color components a and b in ...
详细信息
Different types of partial discharge (PD) cause different damage to gas-insulated switchgear (GIS), so it is very important to correctly identify the type of PD for evaluating the GIS insulation condition. The traditi...
详细信息
Recently, deep neural networks trained with limited amount of labeled data often yield uncertain predictions of patternrecognition tasks. Especially for medical image segmentation, existing methods are prone to produ...
详细信息
ISBN:
(纸本)9789819755936;9789819755943
Recently, deep neural networks trained with limited amount of labeled data often yield uncertain predictions of patternrecognition tasks. Especially for medical image segmentation, existing methods are prone to produce inaccurate predictions in target edge regions due to the low contrast at organ boundaries. To address the above problem, we propose a novel dual consistency regularization network (DC-Net) for semi-supervised medical image segmentation, which can obtain low-entropy decision boundaries by performing consistency predictions under model-level and task-level perturbations. Specifically, our network comprises a shared encoder and multiple decoders with different up-sampling strategies. Each decoder is equipped with two branches for dual-task output. For model consistency, the cross-consistency loss is designed between the segmentation map and the pseudo-labels across different models, aiming to minimize the discrepancy among different model outputs. For task consistency, we promote consistency between the segmentation maps and the pixel-level probability maps transformation from the signed distance maps (SDM), thereby constructing the geometric contours of the target to achieve more precise segmentation boundaries. Experimental results on the public Left Atrium dataset have shown that DC-Net achieved Dice scores of 91.29% and 89.75% with 20% and 10% labeled data respectively, which surpasses the other six current promising methods.
暂无评论