In recent years, the performance of face verification systems has significantly improved using deep convolutional neural networks (DCNNs). A typical pipeline for includes training a network subject classification with softmax loss, penultimate layer output as feature descriptor, and generating cosine similarity score given pair images. The loss function does not optimize features to have higher positive pairs lower negative pairs, which leads gap. this paper, we add an L2-constraint...

The multilayered artificial neural network with learning by back-propagation algorithm configuration is the most common in use, due to of its ease training. It estimated that over 80% all projects development use back-propagation. In algorithm, there are two phases cycle, one propagate input patterns through and other adapt output changing weights network. back-propagation-feed forward can be used many applications such as character recognition, weather financial prediction, face detection...

Foot and mouth disease (FMD) is a contagious viral that has high economic impact on livestock industry affecting large small ruminant. Most research works are carried out hematobiochemical alteration due to FMD virus (FMDV) in bovine but there paucity of literature dearth how FMDV affects the profiles goats. This study was aimed investigate profile Forty two whole blood samples were collected from FMDV-infected (n=32) apparently healthy (n=10) goats estimate alteration. There significant...

In recent years, the performance of face verification and recognition systems based on deep convolutional neural networks (DCNNs) has significantly improved. A typical pipeline for includes training a network subject classification with softmax loss, using penultimate layer output as feature descriptor, generating cosine similarity score given pair images or videos. The loss function does not optimize features to have higher positive pairs lower negative pairs, which leads gap. this paper,...

We present an algorithm for simultaneous face detection, landmarks localization, pose estimation and gender recognition using deep convolutional neural networks (CNN). The proposed method called, HyperFace, fuses the intermediate layers of a CNN separate followed by multi-task learning that operates on fused features. It exploits synergy among tasks which boosts up their individual performances. Additionally, we propose two variants HyperFace: (1) HyperFace-ResNet builds ResNet-101 model...

The implementation of the security system for all devices is through passive communication technology. People from different origins and regions need a their platforms. convincing type that it makes sure works under proper guidance natural care system. leverage to make them work conditions defined process. One-time password-based technology also used other surveillance process wholly monitored by one-time theme. major done superior convenience successive devices. metropolitan areas which are...

Air pollution has a significant impact on environment resulting in consequences such as global warming and acid rain. Toxic emissions from vehicles are one of the primary sources pollution. Assessment air data is critical order to assist residents locating safest areas city that ideal for life. In this work, density-based spatial clustering applications with noise (DBSCAN) used which among widely algorithms machine learning. It not only capable finding clusters various sizes shapes but can...

Cognitive radio (CR) concept is turning out as a prominent approach used in the wireless communication network for increasing spectrum efficiency by opportunistically and mutually sharing of contemporary networks. CR can bear high traffic loads during emergencies major disasters overcoming limitations like lack capacity. The fundamental issues pertaining implementation (CRN) are presence co‐channel interference adjacent channel among users; most importantly to primary users. Effective...

In this work, an Automatic Speech Recognition (ASR) system of isolated words for Maithili dialect is presented. Isolated Word (IWR) systems recognize a spoken word by person through microphone or some other devices. we have centered to perceive utilized telephone security and internet searchers, programmed dialing managing banking frameworks. The speech signals are changed over into arrangement highlight vectors the elements Mel-Frequency Cepstral Coefficients (MFCC). IWR demonstrated with...

Abstract Software is a consequential asset because concrete software needed in virtually every industry, business, and for function. It becomes more paramount as time goes on – if something breaks within your application portfolio expeditious, efficient, efficacious fine-tune needs to transpire anon possible. Therefore, recognizing the faults early phase of development lifecycle essential both, diminishing cost terms efforts money Similarly, important find out features which could be...

A cost-effective and effective agriculture management system is created by utilizing data analytics (DA), internet of things (IoT), cloud computing (CC). Geographic information (GIS) technology remote sensing predictions give users stakeholders access to a variety sensory data, including rainfall patterns weather-related (such as pressure, humidity, temperatures). They have unstructured format for data. The current systems do poor job analysing such since they cannot effectively balance...

Though Convolutional Neural Networks (CNNs) have surpassed human-level performance on tasks such as object classification and face verification, they can easily be fooled by adversarial attacks. These attacks add a small perturbation to the input image that causes network misclassify sample. In this paper, we focus neutralizing compact feature learning. particular, show learning features in closed bounded space improves robustness of network. We explore effect L2-Softmax Loss, enforces...

The conventional text documents have made it possible to efficiently retrieve large amounts of data with the development various search engines. However, these traditional approaches frequently lower accuracy in retrieval, particularly when certain characteristics that call for more in-depth semantic extraction. A engine algorithms called Algorithm Seer has recently been developed. normal collects deep textual metadata and pseudo-codes from research papers. such a system is unable...