With an overwhelming increase in the demand of autonomous systems, especially applications related to intelligent robotics and visual surveillance, come stringent accuracy requirements for complex object recognition. A system that maintains its performance against a change object’s nature is said be sustainable it has become major area research computer vision community past few years. In this work, we present deep learning architecture, which utilizes multi-layer features fusion selection,...

Abstract Effective recognition of fruit leaf diseases has a substantial impact on agro‐based economies. Several exist that badly the yield and quality fruits. A naked‐eye inspection an infected region is difficult tedious process; therefore, it required to have automated system for accurate disease. It widely understood low contrast images affect identification classification accuracy. Here parallel framework real‐time apple disease proposed. Initially, hybrid stretching method increase...

Pakistan’s economy is largely driven by agriculture, and wheat, mostly, stands out as its second most produced crop every year. On the other hand, average consumption of wheat steadily increasing well, due to which exports are not proportionally growing, thereby, threatening country’s in years come. This work focuses on developing an accurate production forecasting model using Long Short Term Memory (LSTM) neural networks, considered be highly for time series prediction. A data...

Abstract Melanoma is considered to be one of the deadliest skin cancer types, whose occurring frequency elevated in last few years; its earlier diagnosis, however, significantly increases chances patients’ survival. In quest for same, a computer based methods, capable diagnosing lesion at initial stages, have been recently proposed. Despite some success, margin exists, due which machine learning community still considers this an outstanding research challenge. work, we come up with novel...

In the era of industry 4.0, safety, efficiency and reliability industrial machinery is an elementary concern in trade sectors. The accurate remaining useful life (RUL) prediction equipment due time allows us to effectively plan maintenance operation mitigate downtime raise revenue business. past decade, data driven based RUL prognostic methods had gained a lot interest among researchers. There exist various deep learning-based techniques which have been used for estimation. One widely...

Abstract Human gait analysis is a novel topic in the field of computer vision with many famous applications like prediction osteoarthritis and patient surveillance. In this application, abnormal behavior problems walking style detected suspected patients. The means assessments terms knee joints any other symptoms that directly affected patients’ style. carries substantial importance medical domain, but variability clothes, viewing angle, carrying conditions, may severely affect performance...

Automated detection of vision threatening eye disease based on high resolution retinal fundus images requires accurate segmentation the blood vessels. In this regard, and finer vessels, which are obscured by a considerable degree noise poor illumination, is particularly challenging. These noises include (systematic) additive multiplicative (speckle) noise, arise due to various practical limitations imaging systems. To address inherent issue, we present an efficient unsupervised vessel...

Federated learning is a distributed method used to solve data silos and privacy protection in machine learning, aiming train global models together via multiple clients without sharing data.The rapid evolution of cyber threats poses significant challenges modern cybersecurity systems their associated legal frameworks. This paper addresses the problem increasingly sophisticated breach methods that outpace traditional defense mechanisms. Data security received great deal research attention...

Segmentation and classification are two imperative, yet challenging tasks in image analysis for remote-sensing applications. In the former, an is divided into spatially continuous, disjoint, homogeneous regions, called clusters, terms of their various properties: shape, intensity, texture, colour, contrast, etc. Classification, on other hand, applied later process, to recognize or categorize individual objects targets. Each task plays important role refinement enhancement utilizations remote...

In this article, a blind data hiding reversible methodology to embed the secret for purpose into cover image is proposed. The key advantage of research work resolve privacy and secrecy issues raised during transmission over internet. Firstly, decomposed sub-bands using integer wavelets. For decomposition, Fresnelet transform utilized which encrypts by choosing unique parameter construct dummy pattern. pattern then embedded an approximated sub-band image. Our proposed method reveals...

Human motion analysis has received a lot of attention in the computer vision community during last few years. This research domain is supported by wide spectrum applications including video surveillance, patient monitoring systems, and pedestrian detection, to name few. In this study, an improved cascaded design for human presented; it consolidates four phases: (i) acquisition preprocessing, (ii) frame segmentation, (iii) features extraction dimensionality reduction, (iv) classification. The...

We propose a novel deep learning architecture, called XcelNet17, for image classification in remote sensing. Comprising fourteen convolutional and three fully connected layers, XcelNet17 outperforms several benchmark architectures available the literature terms of accuracy. Additionally, we present BA-ABC, new hybrid feature selection algorithm that inherits strengths Bat Algorithm (BA) Artificial Bee Colony (ABC) algorithm. Together these contributions significantly enhance performance...

ABSTRACT Increases in the prevalence of melanoma, most lethal form skin cancer, have been observed over last few decades. However, likelihood a longer life span for individuals is considerably improved with early detection this malignant illness. Even though field computer vision has attained certain level success, there still degree ambiguity that represents an unresolved research challenge. In initial phase study, primary objective to improve information derived from input features by...

Considering the effectiveness of outcome-based education and its increasing implementation in higher education, we propose a set course learning outcomes that may be related to any engineering problem, particular final year project undergraduate programs. We also show how these mapped program identified by Washington Accord. Our case study is an embedded vision system developed our own group, which assess against using proposed self-assessment report rubrics. conclude presenting assessment...

Abstract Considering the lack of optimization support for Quantum-dot Cellular Automata, we propose a dynamically reconfigurable logic cell capable implementing various operations by means artificial neural networks. The can be reconfigured to any 2-input combinational gate altering strength connections, called weights and biases. We demonstrate how these cells may appositely organized perform multi-bit arithmetic operations. proposed work is important in that it gives standard...

Salient object detection is typically accomplished by combining the outputs of multiple primitive feature detectors (that output maps or features). The diversity images means that different basic features are useful in contexts, which motivates use complementary a general setting. However, naive inclusion not for particular image leads to reduction performance. In this paper, we introduce four novel measures quality and then those dynamically select combination process. resulting saliency...

Proceeding miniaturization in the VLSI circuits continues to pose challenges conventionally used synchronous design style microprocessors. These include distribution of clock GHz range, robustness delay variations, reduction electromagnetic interference, and energy conservation, name a few. The asynchronous logic has been known for its ability address aforementioned by means closed-loop handshake protocols, instead notorious signals. Because these advantages, there have numerous attempts on...