Canidae

Multi tool use
Multi tool use



































Canidae
Aetas fossilium: 39.75–0 Ma

PreЄ





















Є

O

S

D

C

P

T

I

K

Pg

N







Ab Eocaeno ad Holocaenum


Maiora genera Canidarum quae exstant: Canis, Cuon, Lycaon, Cerdocyon, Chrysocyon, Speothos, Vulpes, Nyctereutes, Otocyon and Urocyon

Taxinomia

Regnum:
Animalia

Phylum:
Chordata

Classis:
Mammalia

Ordo:
Carnivora
Subordo:
Caniformia

Familia:
Canidae
G. Fischer de Waldheim, 1817[1]
Genera


  • Atelocynus

  • Canis

  • Cerdocyon

  • Chrysocyon

  • Cuon

  • Dusicyon

  • Lycalopex

  • Lycaon

  • Nyctereutes

  • Otocyon

  • Speothos

  • Urocyon

  • Vulpes



Canidae sunt familia carnivororum, quae canes, lupos, vulpes, thoes, coiotes, aliaque mammalia canibus similia comprehendit.




Index






  • 1 Pinacotheca


  • 2 Notae


  • 3 Bibliographia


  • 4 Nexus externi





Pinacotheca |






  • Canis aureus







  • Canis lupus







  • Canis lupus rufus







  • Canis pictus







  • Canis latrans







  • Chrysocyon brachyurus







  • Cuon alpinus







  • Nyctereutes procyonoides







  • Otocyon megalotis







  • Urocyon cinereoergentus







  • Vulpes lagopus






Notae |




  1. ↑ Fischer de Waldheim, G. 1817. Adversaria zoologica. Moscuae. 5:368–428. p372



Bibliographia |



  • Corbet, G.B. & Hill, J.E. 1991. A World List of Mammalian Species, Third edition. Natural History Museum Publications & Oxford University Press, London and Oxford.: v-viii, 1-243.

  • Margulis, L. & Schwartz, K.V. 1982. Five Kingdoms. An Illustrated Guide to the Phyla of Life on Earth. W.H.Freeman, San Francisco..

  • McKenna, M.C. & Bell, S.K. 1997. Classification of Mammals Above the Species Level. Columbia University Press, New York.: i-xii, 1-631.

  • Storer, T.I., Usinger, R.L., Stebbins, R.C. & Nybakken, J.W. 1979. General Zoology, Sixth Edition. McGraw-Hill Book Company, New York.: i-ix, 1-902.



Nexus externi |






Wikidata-logo.svg
Situs scientifici:  • ITIS • NCBI • Biodiversity • Encyclopedia of Life • Marine Species • Fossilworks





Wikispecies-logo.svg
 Vide Canidas apud Vicispecies.






Commons-logo.svg
Vicimedia Communia plura habent quae ad Canidas spectant.


.mw-parser-output .stipula{padding:3px;background:#F7F8FF;border:1px solid grey;margin:auto}.mw-parser-output .stipula td.cell1{background:transparent;color:white}




stipula
Haec stipula ad biologiam spectat. Amplifica, si potes!








dP8vEObbXLxISCASJ,1l4r,QWhoS pEEUkpwDimA 19EZ8cXuT,3H5b gUJaDwQ2,lyD6Ay4SA gncXYaV7GXgJ zC,RP7aLw6AV
-
AZoX0Wp86kvh4USE0grD0

Popular posts from this blog

Tabula Rosettana

Image
Tabula multilinguis Rosettana in Museo Britannico ostenditur. Tabula Rosettana, [1] etiam titulo OGIS 90 agnita, est stela decreto de rebus sacris in Aegypto anno 196 a.C.n. lato inscripta. Tabula iuxta Rosettam Aegypti, urbem in delta Nili et ad oram maris Mediterranei iacentem, anno 1799 a milite Francico reperta est. Inventio stelae, linguis duabus scripturisque tribus inscriptae, eruditis Instituti Aegypti statim nuntiata est; ibi enim iussu imperatoris Napoleonis eruditi omnium scientiarum (sub aegide Commissionis Scientiarum et Artium) properaverant cum expeditione Francica. Qua a Britannis mox debellata, tabula Rosettana Londinium missa hodie apud Museum Britannicum iacet. Textus Graecus cito lectus interpretationi textuum Aegyptiorum (in formis hieroglyphica et demotica expressorum) gradatim adiuvit. Denique textum plene interpretatus est Ioannes Franciscus Champollion. Ab opere eruditorum cumulativo coepit hodiernus scripturae hieroglyphicae linguaeque Aegyptiae a...
Read more

How to label and detect the document text images

Image
1 $begingroup$ This is what I mean as document text image: I want to label the texts in image as separate blocks and my model should detect these labels as classes. NOTE: This is how the end result should be like: The labels like Block 1, Block 2, Block 3,.. should be Logo, Title, Date,.. Others, etc. Work done: First approach : I tried to implement this method via Object Detection, it didn't work. It didn't even detect any text. Second approach : Then I tried it using PixelLink. As this model is build for scene text detection, it detected each and every text in the image. But this method can detect multiple lines of text if the threshold values are increased. But I have no idea how do I add labels to the text blocks. PIXEL_CLS_WEIGHT_all_ones = 'PIXEL_CLS_WEIGHT_all_ones' PIXEL_C...
Read more

LSTM sequence prediction: 3d input to 2d output

Image
1 $begingroup$ I have this LSTM model model = Sequential() model.add(Masking(mask_value=0, input_shape=(timesteps, features))) model.add(LSTM(100, dropout=0.2, recurrent_dropout=0.2, return_sequences=False)) model.add(Dense(features, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy']) and shapes X_train (21, 11, 5), y_train (21, 5) . Each timestep is represented by 5 features and return_sequences is set to False because I want to predict one 5D array (the next timestep) for each input sequence of 11 timesteps. I get the error ValueError: y_true and y_pred have different number of output (5!=1) If I reshape the data as X_train (21, 11, 5), y_train (21, 1, 5) instead I get the error ValueError: Inva...
Read more