We all know that there is an exponential growth in the production of digital data. The user of the internet approaches the cloud service providers to upload the video data into the cloud. The cost and size of the digital videos is huge. Hence there is great need for techniques which aims at optimizing the cost and size for storing the data. This paper provides a comprehensive overview of video deduplication system by extracting the global and local features of the video. The major techniques employed in the process of video deduplication are Conv2d i.e., CNN algorithm to extract the local features of the video and hashing algorithms like SHA-256 to extract the global features of the video.
The ability to converse with hearing and deaf persons has always been difficult for those who are tongue-tied. In this paper, we can see different methods which are introduced to help them to communicate effectively. There are many human interpreters or assistant tools to help them communicate, but each person cannot afford that aid. The only mode of communication for them is sign language. Therefore, the project's primary goal is to assist those individuals by providing a system that will recognize the signs, translate them into text, and enable them to lead a normal social life. Previously, a method including hand detection had been developed as a learning tool for novices in sign language. The system was developed using a method based on skin color modeling known as explicit skin-color space thresholding. The specified range of skin tones will distinguish between pixels, or the hand, and non-pixels, or the background. The photos were given as input to a model called the CNN a deep learning algorithm. We will be implementing this project using Keras to train the images. This document provides information on a variety of projects/research on sign language detection in the domains of machine learning, deep learning, and image depth data. This study considers a number of the numerous problems that must be overcome in order to overcome this problem, as well as the future scope.
Underwater images obtained from sea is degraded in its quality due to absorption, scattering, bending of light etc. Red channel compensation is a major process in underwater image restoration which helps in avoiding the effect of red artifacts in the image. In this paper pipelined architecture is developed for red channel compensation unit. The architecture is synthesized for 45nm Technology node and simulated for its functionality verification at 100MHz of operating frequency. The IEEE-754 standard is used to store and access the image from memory. A method is proposed in the designed architecture intended for fast computation and power reduction.
Today as many institutions, corporate organizations, and office campuses lack with an automated Entry control system for unauthorizedvehicles also an efficient automated parkingsystem. This is being done manually with security people, who must go to each vehicle at the main gate and verify, whether the person in the vehicle belongs to that organization or not. Which is really a tediousjob, wastes time, causing congestion at the gate making the authorized person belonging to the organization toexperience the annoying delay at the main gate and also in parking their vehicle. The proposed RFID based IoT solution system in this paper tries to resolve this by allowing the security at the main gate for easily recognizing the authorized employee vehicle and making employee to get the message with appropriate parking slot number to his phone at the entrance itself. This completely avoids the traffic congestion at the gate and the problem of searching for parking slot in the campus or basement. This system also provisions the security staff to have the information on authorized and unauthorized vehicles with the vehicle number and entry time, and manage the parking space or slots effectively.
Hardware inventory management plays a pivotal role in warehouse goods management for several industrial activities. Hardware inventory management helps to track warehouse goods, ensures that there is an adequate amount of goods left back in the inventory, and prevents overstock or shortage of stocks. This paper discusses the above procedure to be implemented with the help of IoT. In this study, the purpose of the application was to serve withless wiring, fewer components, and to make the system be available at a low cost. This system uses NodeMCU ESP8266 module which is an open-source platform having built in Wi-Fi-module feature, which is best suited for IoT related applications. The tracking and stock details were automatically updated on a management systemconnected to the same network as that of the developed system. A detailed graphical representation of the stock availability in a warehouse can be viewed. From the graph, the inventory manager can decide whether to increase the stock quantity or not. The methods that are currently being followed are more human- dependent and not framed with modern technology. Therefore, inventory details are not always accurate, which may also be one of the reasons why a business experiences loss. With this system, the entire process is made more automated, with less human intervention, thereby providing accurate values for inventory goods.
