ROHIT SACHDEVA
@modicollege.com
ASSISTANT PROFESSOR
MULTANI MAL MODI COLLEGE, PATIALA
EDUCATION
MCA, MPhil PhD
RESEARCH INTERESTS
DIGITAL IMAGE PROCESSING
IoT
CLOUD COMPUTING
SPEECH RECOGNITION
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
Loveleena Mukhija, Rohit Sachdeva, and Amanpreet Kaur
Springer Nature Singapore
Amrit Preet Kaur, Amitoj Singh, Rohit Sachdeva, and Vinay Kukreja
Springer Science and Business Media LLC
Loveleena Mukhija and Rohit Sachdeva
IEEE
Virtualization has been proved as a boon for computing in today’s scenario in the cloud. One of the major challenges faced while computing user applications relates to the placement of resources of the data centre especially virtual machines to the physical hosts optimally for successfully completion of users computational tasks. Sustainable use of resources eminently energy efficient and renewable resources contribute to the economies of scale In this paper we apply a KCS algorithm which integrates bio inspired cuckoo search with unsupervised K clustering machine learning algorithm for resolving the VMP problem. The integration of these two algorithms can result in near optimal solution.
Sachin Lodhi, Sakshi Sakshi, Vinay Kukreja, and Rohit Sachdeva
IEEE
Digitalization is required for the industry's evolution in each sub-sector. While the rate of digitalization has had an influence, traditional methods of document storage have been supplanted by digital techniques such as databases, softcopies, and so on. However, certain industries continue to use the conventional technique of storing data, such as hard copies and scanned digital documents. There would be a certainty of the presence of numerous factors, such as noise, background noise, obscured and blurred text, and watermarks, while collecting digital photos from these hard copies and scanned documents. The quality of the acquired image degrades as a result of these factors. Because of the variables listed above, the digital version, i.e., photographs of the physical document, has declined in quality. This article proposes a solution to this problem. The proposed model loosely follows the Encoder-Decoder structure. The model is trained on 2000 images and managed to achieve 66.33% accuracy on the validation set.
Rishabh Sharma, Deepak Kumar, Vinay Kukreja, and Rohit Sachdeva
IEEE
Automatic speech recognition (ASR) has been an active area of research for decades. As demand for ASR systems has been increased in the last few years due to their utility in a wide range of applications. The proposed work intends to develop a Punjabi ASR-based speech classification system using pitch enhancement corps optimization technique and Mel frequency cepstral coefficient (MFCC) feature extraction method. The complete experiment has been conducted on a total of 80 speakers containing comprising 6 hours of speech voice recording corpus. The classification language model resulted in the minimum word error rate (WER) of 8.2% in the case of the tri-gram model with 80 speakers. In addition to this, a comparison of the resulting outcomes has been conducted which present the outperformance of the tri-gram language classification model in the case of all set of speakers.
Amritpreet Kaur, Rohit Sachdeva, and Amitoj Singh
Springer International Publishing
Amritpreet Kaur, Rohit Sachdeva, and Amitoj Singh
Springer International Publishing
S. Sehaj Singh, R. Sachdeva, and R. Sharma
Union of Researchers of Macedonia
In this paper, an integrated enhancement technique is designed for underwater images colour correction and dehazing. In the first step, preprocessing of the image is done and its RGB planes are extracted. Second step comprises the calculation of the exposure values for the Red, Green and Blue colour planes in order to determine the superior, intermediate, and the inferior planes. For the third step, inferior and intermediate planes are enhanced based on the exposure value of the superior plane. Fourth and the last step apply the power-law expression to the inferior channel. The gamma factor for the powerlaw expression is determined using cuckoo search algorithm. In addition, the cuckoo search algorithm gives multiple optimal gamma values in place of one. Thus, we got multiple optimal solutions in the output. The experimental results are performed on the standard dataset images. We have done the qualitative and quantitative analysis. The analysis shows that the proposed technique produces desired results for underwater image enhancement.