Hyper-parameter optimization of Deep Convolutional Networks for object recognition

Recently sequential model based optimization (SMBO) has emerged as a promising hyper-parameter optimization strategy in machine learning. In this work, we investigate SMBO to identify architecture hyper-parameters of deep convolution networks (DCNs) object recognition. We propose a simple SMBO strategy that starts from a set of random initial DCN architectures to generate new architectures, which on training perform well on a given dataset. Using the proposed SMBO strategy we are able to identify a number of DCN architectures that produce results that are comparable to state-of-the-art results on object recognition benchmarks.Comment: 4 pages, 1 figure, 3 tables, Submitted to ICIP 201

Comparison and correlation of visual inspection with acetic acid, papanicolaou smear and colposcopy in detection of precancerous cervical lesions

Background: Cervical cancer is a huge emotional and financial burden on society. To curb the disease, there is a need to develop a screening test that has good sensitivity and specificity. The present study is aimed to compare the effectiveness of the Pap smear, visual inspection with acetic acid (VIA) and colposcopy for mass screening of premalignant and malignant lesions of the cervix. The objective of this study was to screen women of 30-45 years of age for precancerous cervical lesions with VIA, Pap smear and colposcopy. And compare and correlate the findings of Pap smear, colposcopy and VIA in detecting precancerous lesions of cervix.Methods: This was a prospective observational study conducted from 1 January 2015 till 1 June 2016 (36 months) in OPD, department of obstetrics and gynaecology among 500 women of 30-45 years. of age group. Pap smear was performed by the conventional method and then VIA was carried out for all; colposcopy was done in all VIA positive patients.Results: Out of 500 study group, 364 (72.8%) women were VIA negative and 136 (27.2%) were VIA positive. Pap results in VIA negative women were either NILM or normal, none was with intraepithelial lesions. Out of 136 VIA positive women 42 (34%) pap results were LSIL or HSIL and on colposcopy 59 (44.7%) women had CIN I/II/III.Conclusions: These results establish VIA as an effective screening test for cancerous and precancerous conditions of the cervix and thus VIA can be implemented as a single primary screening method. Colposcopy can further interpret the VIA positive lesion with almost 100 % sensitivity, specificity, NPV in high grade lesions.

Farming Systems Diversification in North Konkan Region of Maharashtra — An Economic Analysis

The location-specific existing farming systems have been studied for their profitability and extent of diversification in the North Konkan region of Maharashtra. The study is based on the primary data collected from 360 farmers, as well as secondary data on agro-climatic parameters. The study area has been delineated into different clusters/sub- regions using hierarchical agglomerative method. The farming in the North Konkan region has been found highly varied in nature. The enterprises being followed and farm situations are of different nature across different clusters. The farm economy has also depicted a wide variation as per-farm income has been found to range from ` 1135 to ` 218015 across different farming systems. The most profitable farming systems in study area are: (i) Paddy + Irrigated plantation + Betelvines (B:C ratio, 2.02), (ii) Paddy + Pulses + Dairying + Poultry (B: C ratio, 1.74), (iii) Paddy + Vegetables + Dairying ( B:C ratio,1.62), (iv) Paddy + Irrigated plantations + Rainfed plantation + Dairying (B: C ratio,1.57), (v) Irrigated plantations + Dairying (B:C ratio,1.56), and (vi) Paddy + Irrigated plantations + Flowers (B:C ratio,1.42). The diversification has shown a positive co-relation with profitability which underlines the importance of combination of enterprises.Farming systems, Agricultural diversification, North Konkan region, Farm economy, SPSS, Crop diversification index, Agricultural and Food Policy, Q12, Q15,