Mobile imaging and digital storytelling currently support a growing practice of multimedia communication in the West. In this paper we describe project which explores their benefit East, to non-textual information sharing an Indian village. Local audiovisual story creation activities were carried out one month trial, using 10 customized cameraphones library stories represented on village display. The findings show that system was usable by cross-section community valued for its ability...

This paper proposes a novel approach to initial lesion detection in ultrasound breast images. The objective is automate the manual process of region interest (ROI) labeling computer‐aided diagnosis (CAD). We propose use hybrid filtering, multifractal processing, and thresholding segmentation automated ROI labeling. used 360 images evaluate performance proposed approach. Images were preprocessed using histogram equalization before filtering analysis conducted. Subsequently, was applied on...

An international association advancing the multidisciplinary study of informing systems. Founded in 1998, Informing Science Institute (ISI) is a global community academics shaping future science.

Driver distractions can be categorized into 3 major parts:-visual, cognitive and manual. Visual manual distraction on a driver physically detected. However, assessing is difficult since it more of an "internal" rather than any easily measured "external" distraction. There are several methods available that used to detect Physiological measurements, performance measures (primary secondary tasks) rating scales some the well-known This study focused physiological specifically driver's eye mouth...

Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to recognitions that are solely based on License Plate (ALPR) systems.Several car MMR have been proposed in literature.However these approaches feature detection algorithms can perform sub-optimally under adverse lighting and/or occlusion conditions.In this paper we propose a real time, appearance based, approach using Two Dimensional Linear Discriminant Analysis is capable of addressing...

Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to recognitions that are solely based on Number Plate (ANPR) systems. Several MMR have been proposed in literature. In parallel this, the usefulness of multi-resolution feature analysis techniques leading efficient object classification algorithms received close attention from research community. To this effect, Contourlet transforms can an directional image representation has recently...

In this paper, we present a novel framework for representation of images as combination multiple mid-level feature descriptor based group visual words. The is computed on discriminative patches the image to build lexicon, words which are used represent shape within that image. proposed method has been applied application vehicles make and model recognition. Each make, class represented an over complete sub-lexicon representation. classification performed by comparing probe with learned...

Stuttering is a neurodevelopmental speech disorder that affects 70 million people worldwide, approximately 1% of the whole population. People who stutter (PWS) have common symptoms such as block, interjection, repetition, and prolongation. The speech-language pathologists (SLPs) commonly observe these four groups to evaluate stuttering severity. evaluation process tedious time-consuming for (SLP) (PWS). Therefore, this paper proposes new model events detection may help Our based on log mel...

Stuttering is a prevalent speech disorder affecting millions worldwide. To provide an automatic and objective stuttering assessment tool, Event Detection (SED) under extensive investigation for advanced research applications. Despite significant progress achieved by various machine learning deep models, SED directly from signal still challenging due to speech's heterogeneous overlapped nature. This paper presents novel approach using multi-feature fusion attention mechanisms. The model...

We propose a novel approach to fully automatic lesion boundary detection in ultrasound breast images. The novelty of the proposed work lies complete automation manual process initial Region-of-Interest (ROI) labeling and procedure adopted for subsequent detection. Histogram equalization is initially used pre-process images followed by hybrid filtering multifractal analysis stages. Subsequently, single valued thresholding segmentation stage rule-based identification ROI point interest that as...

This paper presents a novel approach to Vehicle Make & Model Recognition in CCTV video footage. CPD (coherent Point Drift) is used effectively remove skew of vehicles detected as cameras are not specifically configured for the VMMR (Vehicle and Recognition) task may capture at different approaching angles. Also ROI (Region Of Interest) segmentation proposed. A LESH (Local Energy Shape Histogram) feature based vehicle make model recognition with novelty that temporal processing improve...

Stuttering is a neurodevelopmental speech disorder wherein people suffer from disfluency in generation. Recent research has applied machine learning and deep approaches to stuttering recognition classification. However, these studies have focussed on small datasets, generated by limited number of speakers within specific tasks, such as reading. This paper rigorously investigates the effective use eight well-known classifiers, two publicly available datasets (FluencyBank SEP-28k)...

In this paper, we propose a multiple animal tracking system in drone footage that is designed and implemented using Deep Neural Network (DNN) based tracking-by-detection approach. The proposed consists of two main components, namely the sub-system for detection, tracking. detection component, exploit effective use YOLO-V5 to detect individual animals centroid algorithm associate location detected consecutive video frames. performance analyzed on containing herds Arabian Oryx with complex...

We propose a hybrid scheme to implement an object driven, block based algorithm achieve low bit-rate compression of stereo image pairs. The effectively combines the simplicity and adaptability existing techniques with edge/contour extraction technique determine appropriate strategy for various areas right image. Unlike object-based coding such as MPEG-4 developed in video community, proposed does not require any additional shape coding. Instead, arbitrary is reconstructed by matching inside...

This paper presents a novel approach to boundary detection of regions-of-interest (ROI) in ultrasound images, more specifically applied breast images. In the proposed method, histogram equalization is used preprocess images followed by hybrid filtering stage that consists combination nonlinear diffusion filter and linear filter. Subsequently multifractal dimension analyse visually distinct areas image. Finally, using different threshold values, region growing segmentation partition The with...

American College of Radiology introduces a standard in classification, the breast imaging reporting and data system (BIRADS), standardize ultrasound findings, clarify its interpretation, facilitate communication between clinicians. The effective use new technologies to support healthcare initiatives is important current research moving towards implementing computer tools diagnostics process. Initially detailed study was carried out evaluate performance two commonly used appearance based...