Birds are significant bioindicators in the assessment of habitat biodiversity, ecological impacts and ecosystem health. Against backdrop easier bird vocalization data acquisition, with deep learning machine technologies as technical support, exploring recognition classification networks suitable for calls has become focus bioacoustics research. Due to fact that spectral differences among various much greater than between human languages, constructing birdsong based on speech does not yield...

Feature selection plays a very significant role for the success of pattern recognition and data mining. Based on maximal relevance minimal redundancy (mRMR) method, combined with feature subset, this paper proposes an improved (ImRMR) method based subset. In ImRMR, Pearson correlation coefficient mutual information are first used to measure single sample category, factor is introduced adjust weights two measurement criteria. And equal grouping exploited generate candidate subsets according...

Abstract With the intensification of ecosystem damage, birds have become symbolic species ecosystem. Ornithology with interdisciplinary technical research plays a great significance for protecting and evaluating quality. Deep learning shows progress birdsongs recognition. However, as number network layers increases in traditional CNN, semantic information gradually becomes richer detailed disappears. Secondly, global carried by entire input may be lost convolution, pooling, or other...

The demand for precise positioning in noisy environments has propelled the development of research on array antenna radar systems. Although orthogonal matching pursuit (OMP) algorithm demonstrates superior performance signal reconstruction, its application efficacy settings faces challenges. Consequently, this paper introduces an innovative OMP algorithm, DTM_OMP_ICA (a dual-threshold mask based independent component analysis), which optimizes reconstruction framework by utilizing two...

Abstract Pine nuts are not only the important agent of pine reproduction and afforestation, but also commonly consumed nut with high nutritive values. However, it is difficult to distinguish among due morphological similarity species. Therefore, improve quality solve adulteration problem quickly non-destructively. In this study, seven ( Pinus bungeana , yunnanensis thunbergii armandii massoniana elliottii taiwanensis ) were used as study 210 near-infrared (NIR) spectra collected from species...

As important members of the ecosystem, birds are good monitors ecological environment. Bird recognition, especially birdsong has attracted more and attention in field artificial intelligence. At present, traditional machine learning deep widely used recognition. Deep can not only classify recognize spectrums birdsong, but also be as a feature extractor. Machine is often to extracted handcrafted parameters. data samples classifier, directly determines performance classifier. Multi-view...

With the advent of big data era and rapid improvement raw scale, feature selection is basic critical technologies for mining. However, in most studies on methods before, mainly directed to treat single or overall subset, while influence correlation redundancy features subset classification results ignored. In this paper, combination grouping factor analysis (FA), a hybrid method based subsets generation through (FAFS_HFS) proposed. Firstly, generate maximum load (maximum explanatory power)...

Environmental sound recognition has been a hot topic in the domain of audio recognition. How to select optimal feature subsets and enhance performance classification precisely is an urgent problem be solved. Ensemble learning, new kind method presented recently, effective way improve accuracy selection. In this paper, experiments were performed on environmental dataset. An improved based constraint score multimodels ensemble selection methods (MmEnFs) exploited experiments. The experimental...

Birdsongs are highly valuable for bird studies as they provide insights into various aspects such species distribution, population structures, and habitat. Recognizing birdsongs plays a crucial role in conservation efforts. However, manually collecting large number of from the natural environment is expensive time-consuming. Moreover, using limited birdsong data often results low classification accuracy models. To better identification birdsongs, we utilize wavelet transform(WT) to convert...

Birds play a vital and indispensable role in biodiversity environmental conservation. Protecting bird diversity is crucial for maintaining the balance of nature, promoting ecosystem health, ensuring sustainable development. The Broad Learning System (BLS) exhibits an excellent ability to extract highly discriminative features from raw inputs construct complex feature representations by combining nodes enhancement nodes, thereby enabling effective recognition classification various birdsongs....

The classification of bird sounds is important in ecological monitoring. Although extracting features from multiple perspectives helps to fully describe the target information, it urgent deal with enormous dimension and curse dimensionality. Thus, feature selection necessary. This paper proposes a scoring method named MICV (Mutual Information Coefficient Variation), which uses coefficient variation mutual information evaluate each feature’s contribution classification. And then, ERMFT...

HMM (Hidden Markov Model) is a statistical-signal based model, and MFCC (Mel frequency Cepstrum Coefficient) one kind of characteristic parameters, both which are widely used in speech recognition. This paper studies MFCC-HMM bird songs recognition technology. Firstly, it collected through web crawler. Then, audios were preprocessed features extracted. Through differential methods calculation, improved feature parameters obtained, fed into the model to classify different kinds songs....

Multiple classifier system trains different classifiers and combines their predictions to improve the accuracy of classification. This paper explains popular algorithms strategies in multiple system, points out key factors affect performance application system. The experiments are carried on given environmental audio data order compare singular methods with such as Random Forest MCS, well Bagging AdaBoost. experimental results show that technology outperforms obtains better It provides an...

Birds are a kind of environmental indicator organism, which can reflect the changes in ecological environment and biodiversity, recognition birdsongs further help understand protect birds natural environment. Extreme learning machine (ELM) has advantages fast speed good generalization ability, is widely used classification problems. Input layer weights hidden thresholds two key factors affecting ELM performance. As one swarm intelligence optimization methods, differential evolution (DE) be...

Computer Forensics is a research hot topic in the field of computer security with recent increases illegal accesses to system. According procedure forensics, this paper presents frame model analyses source digital evidence. Because feature, it especially critical how secure protection evidence and make forensics have legal recognition ability. From collection phase, transmission phase storage stage, discusses key technologies approaches ensure respectively. Through guidance guarantee each...

For the birdsong recognition based on nonstationary features of pronunciation birds, a method MFCC feature mixing with characteristics song channel listening model is proposed in this paper. Three features, reflecting property vocal tract, are extracted: LPCAS (the all poles tract system), plpsestrum specstrum system) and PLP cepstrum system. In experiment, these three kinds mixed to classification decision tree. The results show that average rate those improved by 4.5%, especially,...

Along with the development of data scale and high complexity sound signals, feature extraction classification methods signals have become a major research hotspot. However, current signal are difficult to accurately stably provide high-precision effect for due complex frequency distribution influence noise. Therefore, robust method based on multi-scale multi-directional Gabor filters Mel cepstral coefficient (MtWGM) was proposed. This performs preprocessing by mixing hard threshold soft...

In the classification of birdsong, effect traditional feature extraction methods and identifying birds through deep learning is still not ideal. Therefore, this paper proposes a birdsong method based on Gabor_Wt image convolutional neural network. According to two-dimensional wavelet spectrogram signal can present more detailed information characteristics birdsong. The obtained by using transform from audio. images are extracted texture with 2D-Gabor filters. With network structure, WT_CNN...

<title>Abstract</title> Recent advancements in audio signal processing and pattern recognition have made bird vocalization classification a key focus bioacoustic research. The success of automated birdsong largely depends on denoising feature extraction. This paper introduces two novel methods, namely improved adaptive wavelet threshold (IAwthr) bidirectional Mel-filter bank (BiFBank), which aim to overcome the limitations traditional methods. IAwthr achieves optimization through...

Self-awareness is an important concept in discussions of consciousness that has received increasing attention. To our knowledge, mirror self-recognition and self-awareness not been studied the white-browed laughing thrush Pterorhinus sannio. In investigation, wild sannio were presented with a test known as (MSR). All birds performed four different displays front we call "look around", "crouch", "jump to top mirror", "shake wings". These behaviours did occur absence mirror. typically are...