Debasis Samal's repositories
Ship-Detection-from-Satellite-Images-using-YOLOV4
Ship detection from remote sensing imagery is a crucial application for maritime security which includes among others traffic surveillance, protection against illegal fisheries, oil discharge control and sea pollution monitoring. This is typically done through the use of an Automated Identification System (AIS), which uses VHF radio frequencies to wirelessly broadcast the ships location, destination and identity to nearby receiver devices on other ships and land-based systems. AIS are very effective at monitoring ships which are legally required to install a VHF transponder, but fail to detect those which are not, and those which disconnect their transponder. So how do you detect these uncooperative ships? This is where satellite imagery can help. Synthetic Aperture Radar (SAR) imagery uses radio waves to image the Earth’s surface. Unlike optical imagery, the wavelengths which the instruments use are not affected by the time of day or meteorological conditions, enabling imagery to be obtained day or night, with cloudy, or clear skies. Satellites are collecting these images which could be used to make algorithms for ship detection and segmentation.
Smart-Notepad-using-WORD2VEC
Smart Notepad - It is a notepad which remembers everything which I asked it to and returns the correct answer whenever I asked it question related to the things which I have asked it to remeber.
TIC-TAC-TOE-Game
TIC-TAC-TOE Game using pyhton
Best-Index
Given an array A of N elements. Choose the best index of this array A. An index of the array is called best if the special sum of this index is maximum across the special sum of all the other indices.
Card-Game---Blackjack
Blackjack is the American variant of a globally popular banking game known as Twenty-One. It is a comparing card game between one or more players and a dealer, where each player in turn competes against the dealer. Players do not compete against each other. It is played with one or more decks of 52 cards, and is the most widely played casino banking game in the world. The objective of the game is to beat the dealer in one of the following ways: -->Get 21 points on the player's first two cards (called a "blackjack" or "natural"), without a dealer blackjack. -->Reach a final score higher than the dealer without exceeding 21; or -->Let the dealer draw additional cards until their hand exceeds 21 ("busted").
Cipher-message
Developed a cipher program to encrypt the message. My cipher must rotate every character in the message by a fixed number making it unreadable by enemies. Given a single line of string 'S' containing alpha, numeric and symbols, followed by a number '0<=N<=1000'. Encrypt and print the resulting string. Note: The cipher only encrypts Alpha and Numeric. (A-Z, a-z, and 0-9) . All Symbols, such as - , ; %, remain unencrypted.
Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
Guessing-Game-Challenge
Write a program that picks a random integer from 1 to 100, and has players guess the number. The rules are: If a player's guess is less than 1 or greater than 100, say "OUT OF BOUNDS" On a player's first turn, if their guess is * within 10 of the number, return "WARM!" * further than 10 away from the number, return "COLD!" On all subsequent turns, if a guess is * closer to the number than the previous guess return "WARMER!" * farther from the number than the previous guess, return "COLDER!" When the player's guess equals the number, tell them they've guessed correctly and how many guesses it took!
Seven-Segment-Display
Imagine number written in seven segment format where each segment was creatted used a matchstick. Example: If we have a number 123 so basically we used 12 matchsticks for this number. So what is the numerically largest value that can be generated by using at most the matchsticks that we currently possess.
Speech-Text-Recognition
Its a basic speech to text recognition or you can say convertion
Generating-Fake-Numbers-using-DCGAN
In this project we have built a model which will generate fake nunbers based on the real numbers using DCGAN as explained above. The dataset used for this project is the MNIST dataset.
Live-Face-mask-detection-using-CNN
Coronavirus has now become the talk of the town, Like most people in the world right now are suffering badly and everyday thousand's of people are dying because of COVID-19, I’m genuinely concerned about them. So, Instead of sitting idle and let negative thoughts grow day by day,I decided to do what I do best .In the above project i used webscrapped data with classes people wearing mask and no mask and trained a resent 50. then i used the model to predict on a webcam feed
Plant-Seedlings-Classification-using-CNN
Can we differentiate a weed from a crop seedling? The ability to do so effectively can mean better crop yields and better stewardship of the environment. Although the issue of identifying weeds from plant seedlings may not seem concerning, it actually can be, as if weeds are left there with the other plants or misidentified to instead be a plant, in the long term, weeds can bring plants to not grow as much as they do consume a portion of their nutrients. This would largely impact agriculture in a negative aspect as plants will not grow to their fullest and there will be less of them, although it depends on the type of weed that is present there is no point in taking a chance. As depending on the type, weeds can cause crop yield loss, taint food and feed crops, can harbor problem insects and crop diseases, and much can also cause many other problems that would impact the harvest. Weeds typically sometimes look very green and identical to plants, which is why it is sometimes difficult to identify 100% accurately from a human perspective. It is estimated that weeds cost $2.5 billion a year in lost agricultural production within Australia which is a tremendous loss of money and agriculture. Weeds are indeed a growing issue within the agriculture industry.
Real-or-Forged-signature-detection-using-Siamese-Network
Signature is one of the most popular and commonly accepted biometric hallmarks that has been used since the ancient times for verifying different entities related to human beings, viz. documents, forms, bank checks, individuals, etc. Therefore, signature verification is a critical task and many efforts have been made to remove the uncertainty involved in the manual authentication procedure, which makes signature verification an important research line in the field of machine learning and pattern recognition. In this notebook, we model a writer independent signature verification task with a convolutional Siamese network.
Decision-Trees-and-Random-Forest-Project---Loan-Data
Lending Club connects people who need money (borrowers) with people who have money (investors). Hopefully, as an investor we would want to invest in people who showed a profile of having a high probability of paying us back. We will try to create a model that will help predict this. Lending club had a very interesting year in 2016, so let's check out some of their data and keep the context in mind. This data is from before they even went public. We will use lending data from 2007-2010 and be trying to classify and predict whether or not the borrower paid back their loan in full.
Digit-Recognition-with-Neural-Network
Built a simple neural network model to classify number
Image-Classification-with-CNN
Built a CNN model to classify the image present in the dataset
Linear-Regression-Project---Ecommerce-company
Ecommerce company based in New York City sells clothing online but they also have in-store style and clothing advice sessions. Customers come in to the store, have sessions or meetings with a personal stylist, then they can go home and order either on a mobile app or website for the clothes they want. The company is trying to decide whether to focus their efforts on their mobile app experience or their website. Lets figure it out.
Logistic-Regression-Project---Advertisement
In this project we will be working with a fake advertising data set, indicating whether or not a particular internet user clicked on an Advertisement. We will try to create a model that will predict whether or not they will click on an ad based off the features of that user.
mlflow-demo
mlflow introductory demo